MIE 1616S Research Topics in Healthcare Engineering

Transcription

1 MIE 1616S Research Topics in Healthcare Engineering Professor: Michael Carter Day/Time: Thursday, 2:00 pm 5:00 pm Location: MB 101 Background: (From 2015 offering. Some topics/papers may be different in 2016.) Healthcare Engineering has existed for decades. In the late 70 s and early 80 s, industrial engineering departments were quite common in hospitals across North America. During the late 80 s and 90 s, for some reason, there was a dramatic decrease in the use of industrial engineers. I suspect that IEs were not working on the issues that were keeping the CEO awake at night. However, the profession has survived, often under the name Management Engineering. The term healthcare engineering is intended to convey the general philosophy of design and analysis concepts applied to building a better healthcare system. There have been a number of changes over the past decade. First, the medical establishment began to recognize that the industry has serious efficiency and operational problems (poor resource utilization, waste of money, high error rates, etc.) Much of this change in attitude has been fostered by groups like the Institute for Healthcare Improvement ( Leaders have begun to realize that industrial engineers have the tools necessary for dealing with these issues. Early work in the field was generally individual projects where industrial engineers were asked to look at scheduling small groups of nurses or operating rooms. Gradually, the scope of the problems considered has grown to include patient flow and bed allocation. Recent projects have considered more strategic decisions involving health policy such as immunization guidelines and system-wide resource allocations. There has been a considerable growth in interest from the medical community and the supply of healthcare management engineering specialists is not keeping pace with the demand. Purpose: The purpose of this course is to provide an overview of current OR research in healthcare and to develop the insight required in order to do relevant and significant research in this field. The course attempts to provide an overview to some of the major research topics in the field, but the course also provides an opportunity for students to demonstrate critical analysis of the literature. Graduate students in this class should have an introductory level background in the necessary tools of OR such as mathematical programming, stochastic processes, queueing theory, statistical modelling, decision analysis and dynamic programming. Students must have sufficient knowledge to be able to read and understand the various papers. The majority of the papers involve applications of OR to healthcare problems.

2 Course Description: This is a seminar-based course in which we will review a variety of papers in the field of healthcare OR. We will survey and evaluate several papers within topic areas and try to identify areas for potential future research. Some papers will be distinctly OR, while others will come from researchers in the field of healthcare policy and healthcare economics. One thing that you will notice as we go through the literature is that the area of healthcare engineering is interdisciplinary in nature, and encourages solutions that are derived from various areas of expertise. This interdisciplinary approach is also encouraged through the many funding bodies that currently support healthcare engineering research in North America. The Canadian Institute of Health Research, CIHR, ( funds the majority of healthcare research in Canada. It is composed of 14 virtual institutes that represent all facets of health research. The Institute of Health Services and Policy Research, IHSPR, is most related to the type of collaborative research discussed above. It supports innovative research, capacity-building and knowledge translation in order to improve health care service delivery. In 2001 and 2004, IHSPR was involved with national consultations on health services priorities entitled Listening for Direction. The result of these consultations was a set of priorities for Canadian researchers in the area of health care policy and management. Of course, not all of the topics are relevant to Healthcare Engineering, but many of the readings and articles discussed in this class will align with the most recent set of priorities: Research Themes Workforce planning, training, and regulation Management of the healthcare workplace Timely access to quality care for all Managing for quality and safety Understanding and responding to public expectations Key Components Value of inter-professional team care in different settings Forecasting models Scopes of practice and health professional regulation Relationship between extent/nature of training and health outcomes How changing demographics are leading to changing expectations in the workplace Factors generating organizational commitment and productivity by healthcare professionals Identification of leaders in healthcare Waiting time management for specialized and diagnostic services Timely access to primary and community care Improving access for rural and remote communities and for minority and vulnerable groups Improving quality, uptake of clinical best practices Improving patient safety, adverse event reduction systems Impact of market-driven influences Interpersonal, attitudinal, cognitive, and risk-perception influences Role of the media in influencing public attitudes and public expectations of health services. Effectiveness of alternative approaches to public engagement

3 Sustainable funding and ethical resource allocation Governance and accountability Managing and adapting to change Linking care across place, time, and settings Linking public health to health service Ethical framework for resource allocation Models for institution-level resource allocation Evidence on system efficiencies and resource redeployment Effects and effectiveness of public-private partnerships Selection, role, and use of individual performance indicators Current organizational frameworks for using performance indicators The link between population-based funding and accountability Implications of foreign experiences of public-private partnerships for Canada Intelligence from regionalization experiences Models and mechanisms of knowledge translation Intra-organizational management structures Improving chronic disease management Caregiver support and informal and voluntary care Technology and chronic disease management Surge capacity: How to organize health services to cope with emergencies? Relationship between specific disease prevention or health promotion products/services on need for traditional healthcare services Public health threats & the need for healthcare/public health professionals Required Materials: All materials for the course will be downloaded from the course website. All articles have been retrieved from University of Toronto library full-text databases. Additional Reference Materials: 1. Brandeau, M, Sainfort, F. and Pierskalla, W.P., Operations Research and Health Care, Kluwer Academic Publishers, Vissers, J. and Beech, R., Health Operations Management: Patient Flow Logistics in Health Care, Routledge: London, Ronen, B. and Pliskin, J.S., Focused Operations Management for Health Services Organizations, Wiley and Sons: San Francisco, Hall, R.W., (ed.) Patient Flow: Reducing Delay In Healthcare Delivery, Springer, Langabeer, J.R., Health care operations management: a quantitative approach to business, Jones & Bartlett Publishing Company, Reid, P.P., Compton, W.D., and Grossman, J.H., Building A Better Delivery System: A New Engineering/Health Care Partnership, National Academy Press; 1 edition (Jan )

4 Date Topic Paper(s) 1 Jan 15 Course Introduction Course Outline Brief overview of Canadian healthcare system Class discussion about how Industrial Engineering fits into each of the priority research themes identified by IHSPR/CIHR. 2 Jan 22 Radiotherapy H. E. Romeijn, R. K. Ahuja, J. F. Dempsey, and A. Kumar, A new linear programming approach to radiation therapy treatment planning problems, Operations Research, 54(2), , Wu B, Ricchetti F, Sanguineti G, Kazhdan M, Simari P, Chuang M, Taylor R, Jacques R, McNutt T. Patient geometry-driven information retrieval for IMRT treatment plan quality control Med Phys Dec;36(12): Jan 29 Emergency medical services 4 Feb 5 Pandemic modeling S. Budge, A. Ingolfsson, and D. Zerom, Empirical analysis of ambulance travel times: The case of Calgary Emergency Medical Services, Management Science, 56(4), , R. Alanis, A. Ingolfsson, and B. Kolfal, A Markov Chain Model for an EMS System with Repositioning, Production and Operations Management, 22(1), pp E. Lee, F. Pietz, B. Benecke, J. Mason and G. Burel, Advancing Public Health and Medical Preparedness with Operations Research, Interfaces, 43(1), 79-98, 2013 D. M. Aleman, T. G. Wibisono, and B. Schwartz, A nonhomogeneous agent-based simulation approach to modeling the spread of disease in a pandemic outbreak, Interfaces, 41(3), , Feb 12 Screening D. Evenden, P.R. Harper, S. Brailsford and V. Harindra, Improving the cost-effectiveness of Chlamydia screening with targeted screening strategies, Journal of the Operational Research Society (2006) 57, N. van de Velde, M. Brisson, and M.-C. Boily, Modeling Human Papillomavirus Effectiveness: Quantifying the Impact of Parameter Uncertainty, American Journal of Epidemiology (2007) Vol. 165, No. 7.,

5 6 Feb 26 Markov decision processes in healthcare 7 Mar 5 Stochastic programming in healthcare 8 Mar 12 Scheduling OR M. Kim, A. Ghate, and M. Phillips, A Markov decision process approach to temporal modulation of dose fractions in radiation therapy, Physics in Medicine and Biology, 54(14), , Z. Erkin, M. D. Bailey, L. M. Maillart, A. J. Schaefer, and M. S. Roberts, Eliciting patients' revealed preferences: An inverse Markov decision process approach, Decision Analysis, 7(4), , O. Y. Ozaltin, O. A. Prokopyev, A. J. Schaefer, and M. S. Roberts, Optimizing the societal benefits of the annual influenza vaccine: A stochastic programming approach, Operations Research, 59(5), , S. H. Jacobson, E. C. Sewell and R. A. Proano, An analysis of the pediatric vaccine supply shortage problem, Health Care Management Science 9: , J. T. Blake and J. Donald, Mount Sinai hospital uses integer programming to allocate operating room time, Interfaces, 32(2): 63, J. Beliën, E. Demeulemeester and B. Cardoen A decision support system for cyclic master surgery scheduling with multiple objectives, J. of Scheduling 12: , Mar 19 Organ transplantation Stanford, D. A., Renouf, E. M.. and McAlister, V. C.. (2008). Waiting for liver transplantation in Canada: waitlist history and sensitivity analysis for the future. Health Care Manage. Sci., D. Bertsimas, V. F. Farias, and N. Trichakis, Fairness, efficiency and flexibility in organ allocation for kidney transplantation, Operations Research 61(1), pp , Mar 26 Data mining in healthcare 11 Apr 2 Emergency Departments G. Phillips-Wren, P. Sharkey, and S. M. Dy, Mining lung cancer patient data to assess healthcare resource utilization, Expert Systems with Applications, 35, , KJ Glowacka, RM Henry, and JH May Hybrid Data Mining/Simulation Approach for Modelling Outpatient No-Shows in Clinic Scheduling Journal of the Operational Research Society 60(8),2009, p D. C. Lane, C. Monefeldt, and J. V. Rosenhead, Looking in the wrong place for healthcare improvements: A system dynamics study of an accident and emergency department, The Journal of the Operational Research Society, 51(5), 518, D. Sinreich and Y. Marmor, Emergency department operations: The basis for developing a simulation tool, IIE Transactions, 37(3), , 2005.

6 12 Apr 16 (maybe) Course Wrap Up Summary of lessons learned and trends seen. Plans for future research. Discussion Seminars: Each seminar will be led by two students. The research will be presented, OR concepts explained and described, and the research compared and critiqued. For most sessions, I have provided two papers that either present similar topics with a different approach or use similar methodologies but with different applications. During your background preparation for the two papers, you may come across other papers that you feel add to the topic and you may certainly discuss those as well. In addition, there are several other files on the web site that you may wish to use as background material, but feel free to bring in any relevant and interesting information that you find. ALL students will read each paper before the presentations and are expected to participate in a meaningful way. Class discussion will run after the presentation; students are expected to bring insights that may not have been developed during the presentation. Students will receive a mark based on their level of participation in each class. The students responsible for presenting the topic/papers should assume that the audience has read the paper and understands it on a basic level. Each student will lead one or two topic discussions depending on the number of students in the course. The final deliverable will be a take-home essay that will build upon the concepts learned in class. It will be no longer than 2000 words. The topic will be handed out on April 2 and essay handed in on April 9. Grading: Class Participation 30% Discussion Leader 30% Take-home Essay 40% (2000 word max) Topic TBA Total 100% Analysis of Papers: When you do your presentation, you may find the following questions help guide a critical analysis of the paper. (Thank you to M. Puterman for his original list that I have added to) Problem: Why was this paper written? What problem was it trying to solve? Is the problem important? Why or why not? Is the problem real or contrived? Is it still relevant? Formulation: How was the problem formulated? Is this the best way possible? What other formulations could be used? Was the level of detail appropriate? Why was this formulation chosen?

7 Methodology and Analysis: Is it appropriate and correct? Why was each step done? (When presenting be sure to go through details at an appropriate level. This doesn't mean repeating derivations or proofs line by line but it does mean that you have to understand them and be able to convey the main ideas.) Results: What are the key results of the paper? Are they complete? Do they address the problem that the paper was trying to solve? Are the results reproducible? Could they be generalized for other problems, locations? Further Directions: What open problems remain and what extensions are possible? How would you follow them up? Are there good research questions that would extend this research? General Assessment of the Paper: Was it well presented? What are its strengths and weaknesses? Comparison of Papers: If both papers used different approaches, which one did you prefer? Under what circumstances would you prefer the other?